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An integrated inertial/celestial navigation system (INS/CNS) has wide applicability in lunar rovers as it provides accurate and autonomous navigational information. Initialization is particularly vital for a INS. This paper proposes a two-position initialization method based on a standard Kalman filter. The difference between the computed star vector and the measured star vector is measured. With the aid of a star sensor and the two positions, the attitudinal and positional errors can be greatly reduced, and the biases of three gyros and accelerometers can also be estimated. The semi-physical simulation results show that the positional and attitudinal errors converge within 0.07″ and 0.1 m, respectively, when the given initial positional error is 1 km and the attitudinal error is 10°. These good results show that the proposed method can accomplish alignment, positioning and calibration functions simultaneously. Thus the proposed two-position initialization method has the potential for application in lunar rover navigation.

Integrating the advantages of INS (inertial navigation system) and the star sensor, the stellar-inertial navigation system has been used for a wide variety of applications. The star sensor is a high-precision attitude measurement instrument; therefore, determining how to validate its accuracy is critical in guaranteeing its practical precision. The dynamic precision evaluation of the star sensor is more difficult than a static precision evaluation because of dynamic reference values and other impacts. This paper proposes a dynamic precision verification method of star sensor with the aid of inertial navigation device to realize real-time attitude accuracy measurement. Based on the gold-standard reference generated by the star simulator, the altitude and azimuth angle errors of the star sensor are calculated for evaluation criteria. With the goal of diminishing the impacts of factors such as the sensors’ drift and devices, the innovative aspect of this method is to employ static accuracy for comparison. If the dynamic results are as good as the static results, which have accuracy comparable to the single star sensor’s precision, the practical precision of the star sensor is sufficiently high to meet the requirements of the system specification. The experiments demonstrate the feasibility and effectiveness of the proposed method.

An improved method for the inertial measurement unit (IMU) calibration of coarse alignment for the low-accuracy attitude heading reference system (AHRS) is proposed in this paper. The sensitivities of the Euler angles with respect to the inertial sensor biases are studied based on the analytic coarse alignment principle, and the errors of earth rotation rate and local gravity in the body frame caused by initial attitude error are analyzed. Then, an improved analytic coarse alignment algorithm with accelerometer and gyro bias calibration in an arbitrary three-position is proposed. Simulation and experiment results show that the novel method can calibrate accelerometer and gyro biases, reduce Euler angle attitude error, and improve navigation precision in practical applications. Moreover, this method can be applied to other low-accuracy inertial navigation systems.

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